Ren Gaocan, Huang Pingping, Ding Yanqiu, Ma Xiaochang
Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Graduate School, China Academy of Chinese Medical Sciences, Beijing, China.
BMC Pharmacol Toxicol. 2025 Feb 7;26(1):27. doi: 10.1186/s40360-025-00867-6.
By using the FAERS database, we aim to identify and assess risk signals of adverse drug events (ADEs) potentially causing pericardial effusion, to inform clinical drug management and promote rational drug use.
We obtained reports of pericardial effusion events from the FAERS database spanning from the first quarter of 2004 to the second quarter of 2024, and identified the top 50 drugs ranked by report frequency or signal strength. Four algorithms, namely the reported odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS), were employed for signal detection of these drugs. Furthermore, for drugs with positive signals, we conducted sensitivity analyses and employed the Weibull shape parameter test to perform a time to onset (TTO) analysis.
We identified 20,057 ADEs related to pericardial effusion, involving 19,693 patients for analysis. The patient population comprised 10,187 males (51.7%) and 7,939 females (40.3%). Adults aged 18-65 years were the largest group (7,798 cases, 39.6%). Regarding clinical outcomes, 9,924 patients (50.4%) experienced hospitalization, and 2,770 cases (14.1%) resulted in death. Ranked by the ROR risk signal strength, the top 3 drugs were hydralazine [ROR (95% CI): 27.11 (22.28-33)], dasatinib [ROR (95% CI): 15.62 (14.07-17.33)], and mesalazine [ROR (95% CI): 8.99 (6.84-11.8)]. We conducted a TTO analysis for the 26 drugs with positive signals. The median TTO and interquartile range (IQR) for the top 3 drugs causing the earliest pericardial effusion were: cytarabine 14 (7.5,38), selexipag 14.5 (4.25, 157.75), dabigatran etexilate 29 (9, 229). Most drugs exhibited an early failure type.
This study systematically compiled a list of drugs with potential risks of causing pericardial effusion. There is a significant association between pericardial effusion and the use of hydralazine, dasatinib, and mesalazine. Moreover, pericardial effusion is more common in patient groups receiving treatments with antineoplastic and immunomodulating agents.
通过使用美国食品药品监督管理局不良事件报告系统（FAERS）数据库，我们旨在识别和评估可能导致心包积液的药物不良事件（ADEs）的风险信号，为临床药物管理提供信息并促进合理用药。
我们从FAERS数据库中获取了2004年第一季度至2024年第二季度的心包积液事件报告，并确定了报告频率或信号强度排名前50的药物。采用四种算法，即报告比值比（ROR）、比例报告比（PRR）、贝叶斯置信传播神经网络（BCPNN）和多项伽马泊松收缩器（MGPS），对这些药物进行信号检测。此外，对于有阳性信号的药物，我们进行了敏感性分析，并采用威布尔形状参数检验进行发病时间（TTO）分析。
我们识别出20,057例与心包积液相关的ADEs，涉及19,693例患者进行分析。患者群体包括10,187名男性（51.7%）和7,939名女性（40.3%）。18至65岁的成年人是最大的群体（7,798例，39.6%）。关于临床结果，9,924例患者（50.4%）住院，2,770例（14.1%）导致死亡。按ROR风险信号强度排名，前三种药物是肼屈嗪[ROR（95%CI）：27.11（22.28 - 33）]、达沙替尼[ROR（95%CI）：15.62（14.07 - 17.33）]和美沙拉嗪[ROR（95%CI）：8.99（6.84 - 11.8）]。我们对26种有阳性信号的药物进行了TTO分析。导致最早心包积液的前三种药物的中位TTO和四分位间距（IQR）为：阿糖胞苷14（7.5, 38）、司来帕格14.5（4.25, 157.75）、达比加群酯29（9, 229）。大多数药物表现为早期失效类型。
本研究系统地编制了一份具有导致心包积液潜在风险的药物清单。心包积液与肼屈嗪、达沙替尼和美沙拉嗪的使用之间存在显著关联。此外，心包积液在接受抗肿瘤和免疫调节药物治疗的患者群体中更为常见。
